๐๐๐ ๐๐๐๐๐๐จ๐ฉ ๐ฅ๐ง๐ค๐๐ก๐๐ข ๐๐ฃ ๐ผ๐ ๐ง๐๐๐๐ฉ ๐ฃ๐ค๐ฌ ๐๐จ๐ฃโ๐ฉ ๐๐ช๐๐ก๐๐๐ฃ๐ ๐๐๐๐ฃ๐ฉ๐จ.
Itโs making money from them consistently.
Most AI infrastructure projects stop at deployment.
$0G is pushing further into monetization.
And honestly, thatโs where things start getting interesting.
The stack already handles:
โ compute
โ storage
โ data availability
โ trusted execution
Meaning builders donโt need to stitch together 10 different services just to get an AI agent running properly.
That alone removes massive friction.
But the more important layer is what happens ๐๐๐ฉ๐๐ง deployment.
#0G is building monetization rails directly into the environment itself.
Deploy the agent.
Launch the token.
Generate revenue.
All inside one ecosystem.
That changes the incentive structure completely.
$SOL showed how ecosystems explode once builders can deploy products cheaply and at scale.
$FET proved markets reward infrastructure tied directly to real AI utility.
0G is combining both ideas into decentralized AI deployment.
And the timing matters.
Because the next AI wave probably wonโt be won by the smartest demos.
Itโll be won by ecosystems where creators can actually earn.
Thatโs how platforms scale.
Not through hype.
Through economic gravity.
A $100M annualized revenue ambition sounds aggressive.
But if AI agents become commercially active at scale, that number suddenly stops sounding unrealistic.
#0glabs